Browsing by Subject "Dynamic Modeling"

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    Dynamic Modeling and Passivity-Based Control of a 2 DOF Tower Crane with a Flexible Hoist Cable
    (2020-08) Shen, Ping-Yen
    Tower cranes are ubiquitous with the construction of modern infrastructure owing to high payload capacity, operational flexibility, and efficiency. This thesis aims to find a solution to achieving quick payload maneuver trajectory with reduced oscillations, and ensuring applicability to autonomous tower cranes that feature noncolocation, underactuation, and uncertain dynamics. A dynamic model of a 2 DOF tower crane is presented accounting for the winch inertia and the axial cable stiffness that varies with the length of the cable using a Rayleigh-Ritz discretization approach. The two proposed control methods, mu-tip control and adaptive sliding-mode control, employ passivity-based control to provide rigorous robust guarantees of closed-loop input-output stability when performing trajectory tracking of a tower crane's payload. The use of the mu-tip rate for trajectory tracking of the crane's payload greatly simplifies the task of designing a stabilizing feedback controller. The proposed mu-tip control uses a mu-tip modification to establish a passive input-output mapping of a 2 DOF tower crane with a flexible hoist cable from a modified force input to the payload's mu-tip rate by considering the sway angle as a flexible coordinate. However, the mu-tip control method relies on the assumptions that the sway angle and its angular rate remain small. A robust sliding-mode-inspired passivity-based control with an adaptive update law that does not rely on a specific structure of the dynamic equations or exact knowledge of the crane's mass properties is presented including experimental validations. A formulation of the adaptive sliding-mode control in the payload coordinates, which facilitates the generation of desired trajectories and the choice of control gains, is presented. The control theory developed in this thesis is not limited to only tower cranes, and can be extended to cable-driven robots and flexible robotic manipulators.
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    Modeling, Control and Optimization of a Novel Compressed Air Energy Storage System for Off-Shore Wind Turbines
    (2016-08) Saadat, Mohsen
    Integrating wind and solar energy into the electric power grid is challenging due to variations in wind speed and solar intensity. Moreover, to maintain the stability of electric power grid, there must be always a balance between the energy production and consumption which is not easy since both of them undergo drastic variation over time. Large scale energy storage systems can solve these issues by storing the extra energy when supply exceeds demand power, and regenerating energy and send it to the electric grid when demand power surpasses the supply. This dissertation focuses on the optimal design and control of a new type of Com- pressed Air Energy Storage (CAES) system that is especially applicable to off-shore wind turbines. The system is designed such that it addresses the need for a compact and energy dense storage system with high roundtrip efficiency for large-scale energy storage applications. The contributions of this work are also beneficial for designing power dense gas compressors/expanders with high thermal efficiency. The material of this thesis can be divided into two parts: In the first part, different approaches and techniques are studied to increase the power density of a liquid piston air compressor/expander system without sacrificing its efficiency. These methods are then combined and optimized in the form of a single design to maximize the performance of an air compressor/expander unit which is the most critical component of the energy storage system under investigation. In the second part, component-level and supervisory-level controllers are designed and developed for the combined wind turbine and energy storage system such that both short-term and long-term objectives are achieved. Improvement of thermal efficiency of an air compressor/expander is achievable by increasing heat transfer between air under compression/expansion and its surrounding solid material in the compression/expansion chamber. This will prevent heat loss by reducing air temperature rise/drop during the compression/expansion phase. Here, liquid piston (instead of conventional solid piston) is used in the compression/expansion chamber where the chamber volume is filled with porous material that increases heat transfer area by an order of magnitude, and therefore improves the thermal efficiency. Since the liquid piston is driven by a variable displacement pump/motor, optimal compression/expansion trajectories are calculated and applied to further increase heat transfer and improve the performance of the system. This improvement is verified both analytically and experimentally. Based on numerical results, utilizing porous material in the compression/expansion chamber with optimized distribution, combined with the corresponding optimal compression/expansion trajectory has the potential to increase the power density by more than 20 folds, without reducing its thermal efficiency. An alternative method to increase heat transfer is to introduce micro-size water droplets (through water spray) in the chamber during air compression/expansion process. Since water has a high heat capacity, the generated heat during compression can be absorbed by water and therefore reduce the temperature rise of air during compression. The same phenomenon but in opposite direction happens in expansion case (heat transfer from water droplets to air) that prevents air from getting very cold which causes poor efficiency. A numerical model is developed and used to study the effect of water spray amount and timing on the thermal performance of air compressor/expander. The opti- mal timing of water spray is calculated to maximize the effectiveness of a given amount of water that is sprayed into the air. The optimally designed liquid piston air compressor/expander unit is then combined with the other components of energy storage system, as well as a wind turbine. Nonlinear techniques are used to design plant-level controllers in order to coordinate different parts in the system, and to achieve both short term objectives (maintaining the frequency of electric generator while capturing maximum wind power) and long term objectives (tracking the power demanded from electric grid and regulating the pressure in the storage vessel). Finally, the combined wind turbine and energy storage system is studied for maximizing the total achievable revenue by optimizing the storage/regeneration sequence according to varying electricity price and available wind power (given storage size and its nominal power). According to the results, an increase of up to 137% in total revenue is achievable by equipping a conventional wind turbine with a CAES system while tracking the calculated optimal storage/regeneration sequence. Additionally, by incorporating the price of different components of energy storage system, a study is conducted to find the effect of system size on maximum achievable revenue that can lead to the economical size selection of the energy storage system.